DocumentCode :
3045639
Title :
Average consensus algorithms robust against channel noise
Author :
Pescosolido, Loreto ; Barbarossa, Sergio ; Scutari, Gesualdo
Author_Institution :
INFOCOM Dept., Univ. of Rome La Sapienza, Rome
fYear :
2008
fDate :
6-9 July 2008
Firstpage :
261
Lastpage :
265
Abstract :
Average consensus algorithms have attracted popularity in the wireless sensor network scenario as a simple way to compute linear combinations of the observations gathered by the sensors, in a totally decentralized fashion, i.e., without a fusion center. However, average consensus techniques involve the iterated exchange of data among sensors. In a practical implementation, this interaction is affected by noise. The goal of this paper is to bring some common adaptive signal processing techniques into the sensor network context in order to robustify the iterative exchange of data against communication noise. In particular, we will compare the performance of two algorithms: (a) a method, reminiscent of stochastic approximation algorithms, using a decreasing step size, with proper decaying law, and (b) a leakage method imposing that the consensus cannot be too distant from the initial measurements. We provide a theoretical analysis, validated by simulation results, of both methods to show how to derive the best tradeoff between the system parameters in order to get the minimum estimation variance, taking into account both observation and interaction noise.
Keywords :
adaptive signal processing; approximation theory; iterative methods; stochastic processes; wireless channels; wireless sensor networks; adaptive signal processing; average consensus algorithm; channel noise; communication noise; interaction noise; iterative data exchange; leakage method; minimum estimation variance; observation noise; stochastic approximation algorithm; wireless sensor network; Adaptive signal processing; Approximation algorithms; Computer networks; Context; Iterative algorithms; Noise robustness; Sensor fusion; Signal processing algorithms; Stochastic resonance; Wireless sensor networks; TBMA; consensus algorithms; sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Advances in Wireless Communications, 2008. SPAWC 2008. IEEE 9th Workshop on
Conference_Location :
Recife
Print_ISBN :
978-1-4244-2045-2
Electronic_ISBN :
978-1-4244-2046-9
Type :
conf
DOI :
10.1109/SPAWC.2008.4641610
Filename :
4641610
Link To Document :
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